Fundamental properties of intrinsic gettering of iron in a silicon wafer

Aoki, Masaki; Hara, Akito; Ohsawa, Akira

doi:10.1063/1.351764

Cited by 79 publications

(70 citation statements)

References 11 publications

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“…The transition between phosphorus diffusion temperature and post-deposition anneal is governed by the solubility difference between the bulk and the emitter and is thus solubility-limited, and the similar [Fe,] at the beginning of the cooldown leads to similar [Fe,] Model predictions after the cooldown. For these time-temperature profile parameters, the [Fe,] at the beginning of the 600 °C anneal is close to the solid solubility (^10 10 cm~3) [40], so no significant change in [Fe,] or precipitates is observed during the low-temperature plateau. The relative invariance of the precipitate distribution during a post-PDG anneal has also been observed experimentally [88].…”

Section: Different Pdg Approaches (Preanneal Peak Standard Pdg Annementioning

confidence: 99%

“…We simulate phosphorus in-diffusion and gettering from both wafer surfaces. The local iron solid solubility in silicon, C s , is provided by Aoki et al [40]. Although strain in the silicon lattice at structural defects can enhance the solid solubility of iron [26,41], we neglect this enhancement because it has only a minor effect on the iron distribution.…”

Section: Systematic Variation Of Model Elementsmentioning

confidence: 99%

“…For the Ham's law Model, the equilibrium iron concentration, Cnq, is the solid solubility of iron, Cs, as defined in [40]. The precipitates are modeled as spheres with the volume of a unit cell containing a single iron atom in a /?-FeSÍ2 precipitate, V v = 3.91 x 10 23 cm 3 .…”

Section: Appendix 2: Detailed Description Of Precipitation Equations mentioning

confidence: 99%

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Building intuition of iron evolution during solar cell processing through analysis of different process models

et al. 2015

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An important aspect of Process Simulators for photovoltaics is prediction of defect evolution during device fabrication. Over the last twenty years, these tools have accelerated process optimization, and several Process Simulators for iron, a ubiquitous and deleterious impurity in silicon, have been developed. The diversity of these tools can make it difficult to build intuition about the physics governing iron behavior during processing. Thus, in one unified software environment and using self-consistent terminology, we combine and describe three of these Simulators. We vary structural defect distribution and iron precipitation equations to create eight distinct Models, which we then use to simulate different stages of processing. We find that the structural defect distribution influences the final interstitial iron concentration ([Fe,]) more strongly than the iron precipitation equations. We identify two regimes of iron behavior: (1) diffusivity-limited, in which iron evolution is kinetic ally limited and bulk [Fe,] predictions can vary by an order of magnitude or more, and (2) solubility-limited, in which iron evolution is near thermodynamic equilibrium and the Models yield similar results. This rigorous analysis provides new intuition that can inform Process Simulation, material, and process development, and it enables scientists and engineers to choose an appropriate level of Model complexity based on wafer type and quality, processing conditions, and available computation time.

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Section: Different Pdg Approaches (Preanneal Peak Standard Pdg Annementioning

confidence: 99%

Section: Systematic Variation Of Model Elementsmentioning

confidence: 99%

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Building intuition of iron evolution during solar cell processing through analysis of different process models

et al. 2015

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“…The interstitial iron concentrations for wafers contaminated with 2·10 14 cm -3 were lower for each gettering condition than similar wafers that were prepared with a lower initial total iron concentration of 10 13 cm -3 , suggesting that precipitation played a role in the gettering process. However, interstitial concentrations remain above the solid solubility in p-type silicon at the gettering temperature [3], [4]. Secondary-ion mass spectrometry indicates an anomalously high iron concentration just below the surface [2].…”

Section: Introductionmentioning

confidence: 99%

Iron precipitation upon gettering in phosphorus-implanted Czochralski silicon and its impact on solar cell performance

Fenning

Vähänissi

Hofstetter

et al. 2014

2014 IEEE 40th Photovoltaic Specialist Conference (PVSC)

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Abstract-Phosphorus implantation can provide a direct route to a high-performing emitter, with no surface dead layer and improved blue response, and potentially higher open-circuit voltage. Here, iron precipitation during gettering is investigated in phosphorus-implanted, low-oxygen monocrystalline silicon and its impact on device performance evaluated. Previously, it has been shown that higher levels of initial iron contamination lead to lower final interstitial iron concentration after gettering with ionimplanted emitters, resulting in longer final bulk diffusion lengths in the more-highly contaminated materials. In this contribution, we show that despite longer bulk diffusion lengths, the open circuit-voltage of devices made from the highly iron-contaminated material can be strongly reduced. Using synchrotron-based Xray fluorescence we reveal the presence of micron-sized iron precipitates in the near surface region. While not measured over wafer-sized areas, the density of these precipitates correlates with the annealing profile. Slow-cooling from the activation anneal and proceeding directly to a 620-750• C gettering anneal results in large precipitates that are indicated as the underlying cause for the disastrous open-circuit voltage. On the other hand, quickly cooling to room temperature and then re-inserting the wafers for gettering results in very small precipitates that do not appear to have significant detrimental affects on open-circuit voltage. It is thus critical to consider the precipitation behavior of iron during gettering of ion-implanted emitters -even in monocrystalline silicon -and during low-temperature annealing in general.

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“…Gettering techniques, such as intrinsic gettering (IG) and extrinsic gettering (EG), are necessary to address these issues. [7][8][9][10][11][12] However, the thermal heat treatment of devices is tending toward short times and low temperatures. 13) Thus, it is difficult for metallic impurities to diffuse to the gettering sink in the silicon bulk.…”

Section: Introductionmentioning

confidence: 99%

Effect of dose and size on defect engineering in carbon cluster implanted silicon wafers

Okuyama¹,

Masada²,

Shigematsu³

et al. 2017

Jpn. J. Appl. Phys.

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REGULAR PAPERS • OPEN ACCESSEffect of dose and size on defect engineering in carbon cluster implanted silicon wafers Carbon-cluster-ion-implanted defects were investigated by high-resolution cross-sectional transmission electron microscopy toward achieving high-performance CMOS image sensors. We revealed that implantation damage formation in the silicon wafer bulk significantly differs between carbon-cluster and monomer ions after implantation. After epitaxial growth, small and large defects were observed in the implanted region of carbon clusters. The electron diffraction pattern of both small and large defects exhibits that from bulk crystalline silicon in the implanted region. On the one hand, we assumed that the silicon carbide structure was not formed in the implanted region, and small defects formed because of the complex of carbon and interstitial silicon. On the other hand, large defects were hypothesized to originate from the recrystallization of the amorphous layer formed by high-dose carbon-cluster implantation. These defects are considered to contribute to the powerful gettering capability required for high-performance CMOS image sensors.

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Fundamental properties of intrinsic gettering of iron in a silicon wafer

Cited by 79 publications

References 11 publications

Building intuition of iron evolution during solar cell processing through analysis of different process models

Building intuition of iron evolution during solar cell processing through analysis of different process models

Iron precipitation upon gettering in phosphorus-implanted Czochralski silicon and its impact on solar cell performance

Effect of dose and size on defect engineering in carbon cluster implanted silicon wafers

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